Soyabeans — Food by country
A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply...
What the numbers show
Soyabeans — Food is currently reported for 182 countries. The highest value is 7,934 1000 t in China; the lowest is 0 1000 t in Micronesia (Federated States of).
The median across all reporting countries is 0 1000 t, and the mean is 115.56 1000 t.
Over the past decade 38 countries rose and 28 fell. The largest increase was in Burkina Faso (up 356.2%), and the largest decrease in Belgium (down 100.0%).
Soyabeans — Food: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 7,934 1000 t | 2023 | up 68.6% | rising |
| 2 | China, mainland | 7,708 1000 t | 2023 | up 75.6% | rising |
| 3 | Indonesia | 2,626 1000 t | 2023 | up 9.2% | rising |
| 4 | Viet Nam | 533 1000 t | 2023 | up 64.0% | rising |
| 5 | Republic of Korea | 309 1000 t | 2023 | down 16.9% | falling |
| 6 | Nigeria | 300 1000 t | 2023 | up 119.0% | rising |
| 7 | India | 267 1000 t | 2023 | up 54.3% | rising |
| 8 | China, Taiwan Province of | 207 1000 t | 2023 | down 30.3% | falling |
| 9 | Thailand | 136 1000 t | 2023 | up 12.4% | rising |
| 10 | Bangladesh | 125 1000 t | 2023 | up 48.8% | rising |
| 11 | Malaysia | 93 1000 t | 2023 | down 6.1% | falling |
| 12 | Zambia | 87 1000 t | 2023 | up 31.8% | rising |
| 13 | Germany | 76 1000 t | 2023 | up 5.6% | rising |
| 14 | Burkina Faso | 73 1000 t | 2023 | up 356.2% | volatile |
| 15 | Democratic People's Republic of Korea | 65 1000 t | 2018 | down 35.0% | falling |
| 16 | Austria | 35 1000 t | 2023 | up 94.4% | rising |
| 17 | Canada | 34 1000 t | 2023 | up 9.7% | rising |
| 18 | Rwanda | 31 1000 t | 2023 | up 47.6% | rising |
| 19 | Afghanistan | 30 1000 t | 2023 | — | volatile |
| 19 | Peru | 30 1000 t | 2023 | up 30.4% | rising |
| 21 | Myanmar | 27 1000 t | 2023 | up 22.7% | rising |
| 22 | Democratic Republic of the Congo | 24 1000 t | 2023 | up 26.3% | rising |
| 23 | Malawi | 23 1000 t | 2023 | down 32.4% | falling |
| 24 | Colombia | 19 1000 t | 2023 | up 11.8% | falling |
| 25 | Angola | 18 1000 t | 2023 | up 200.0% | volatile |
| 26 | China, Hong Kong SAR | 17 1000 t | 2023 | down 15.0% | falling |
| 27 | Tunisia | 16 1000 t | 2023 | down 15.8% | falling |
| 28 | Philippines | 13 1000 t | 2023 | up 225.0% | volatile |
| 29 | Jordan | 9 1000 t | 2023 | — | volatile |
| 29 | Kenya | 9 1000 t | 2023 | unchanged | falling |
| 29 | Panama | 9 1000 t | 2023 | up 125.0% | rising |
| 29 | Australia and New Zealand | 9 1000 t | 2023 | up 50.0% | rising |
| 33 | Ethiopia | 8 1000 t | 2023 | down 84.6% | volatile |
| 34 | Cuba | 7 1000 t | 2019 | up 40.0% | volatile |
| 34 | Bolivia (Plurinational State of) | 7 1000 t | 2023 | — | volatile |
| 36 | Australia | 6 1000 t | 2023 | up 50.0% | rising |
| 36 | France | 6 1000 t | 2023 | up 100.0% | rising |
| 36 | Turkmenistan | 6 1000 t | 2023 | — | volatile |
| 36 | United Kingdom of Great Britain and Northern Ireland | 6 1000 t | 2023 | up 100.0% | rising |
| 40 | Czechia | 5 1000 t | 2023 | down 44.4% | rising |
| 40 | El Salvador | 5 1000 t | 2023 | unchanged | flat |
| 40 | Lao People's Democratic Republic | 5 1000 t | 2023 | unchanged | falling |
| 43 | Belize | 4 1000 t | 2023 | up 300.0% | volatile |
| 43 | Botswana | 4 1000 t | 2023 | up 100.0% | rising |
| 43 | Mozambique | 4 1000 t | 2023 | — | volatile |
| 43 | Poland | 4 1000 t | 2023 | up 100.0% | rising |
| 47 | Bosnia and Herzegovina | 3 1000 t | 2023 | down 25.0% | falling |
| 47 | Spain | 3 1000 t | 2023 | up 200.0% | rising |
| 47 | Italy | 3 1000 t | 2023 | up 200.0% | volatile |
| 47 | Liberia | 3 1000 t | 2023 | up 50.0% | rising |
| 47 | Mexico | 3 1000 t | 2023 | up 50.0% | rising |
| 47 | New Zealand | 3 1000 t | 2023 | up 50.0% | rising |
| 47 | Saudi Arabia | 3 1000 t | 2023 | up 200.0% | rising |
| 47 | Zimbabwe | 3 1000 t | 2023 | unchanged | flat |
| 47 | Timor-Leste | 3 1000 t | 2023 | up 200.0% | rising |
| 47 | Caribbean | 3 1000 t | 2023 | down 91.7% | volatile |
| 47 | Russian Federation | 3 1000 t | 2023 | down 50.0% | falling |
| 58 | Switzerland | 2 1000 t | 2023 | down 50.0% | rising |
| 58 | Chile | 2 1000 t | 2023 | up 100.0% | rising |
| 58 | Costa Rica | 2 1000 t | 2023 | down 71.4% | volatile |
| 58 | Senegal | 2 1000 t | 2023 | — | volatile |
| 58 | Melanesia | 2 1000 t | 2023 | up 100.0% | volatile |
| 63 | United Arab Emirates | 1 1000 t | 2023 | unchanged | rising |
| 63 | Denmark | 1 1000 t | 2023 | — | volatile |
| 63 | Ghana | 1 1000 t | 2023 | — | volatile |
| 63 | Guatemala | 1 1000 t | 2023 | — | volatile |
| 63 | Ireland | 1 1000 t | 2023 | unchanged | falling |
| 63 | Israel | 1 1000 t | 2023 | unchanged | flat |
| 63 | Kazakhstan | 1 1000 t | 2023 | — | volatile |
| 63 | Mauritius | 1 1000 t | 2023 | — | volatile |
| 63 | New Caledonia | 1 1000 t | 2023 | — | volatile |
| 63 | Norway | 1 1000 t | 2023 | — | volatile |
| 63 | Papua New Guinea | 1 1000 t | 2023 | — | volatile |
| 63 | Slovenia | 1 1000 t | 2023 | down 50.0% | volatile |
| 63 | Sweden | 1 1000 t | 2023 | unchanged | rising |
| 63 | Samoa | 1 1000 t | 2023 | — | volatile |
| 63 | Micronesia | 1 1000 t | 2023 | — | volatile |
| 63 | Polynesia | 1 1000 t | 2023 | — | rising |
| 63 | Syrian Arab Republic | 1 1000 t | 2023 | down 96.6% | volatile |
| 63 | Türkiye | 1 1000 t | 2023 | — | volatile |
| 63 | Côte d'Ivoire | 1 1000 t | 2023 | — | volatile |
| 63 | China, Macao SAR | 1 1000 t | 2023 | unchanged | rising |
| 83 | Albania | 0 1000 t | 2023 | — | flat |
| 83 | Argentina | 0 1000 t | 2023 | — | flat |
| 83 | Armenia | 0 1000 t | 2023 | — | flat |
| 83 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 83 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 83 | Belgium | 0 1000 t | 2023 | down 100.0% | falling |
| 83 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 83 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 83 | Bahamas | 0 1000 t | 2023 | — | flat |
| 83 | Belarus | 0 1000 t | 2023 | down 100.0% | falling |
| 83 | Brazil | 0 1000 t | 2023 | — | flat |
| 83 | Barbados | 0 1000 t | 2023 | — | flat |
| 83 | Bhutan | 0 1000 t | 2023 | — | flat |
| 83 | Cameroon | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Congo | 0 1000 t | 2023 | — | flat |
| 83 | Comoros | 0 1000 t | 2023 | — | flat |
| 83 | Cyprus | 0 1000 t | 2023 | — | flat |
| 83 | Djibouti | 0 1000 t | 2023 | — | flat |
| 83 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 83 | Algeria | 0 1000 t | 2023 | — | flat |
| 83 | Ecuador | 0 1000 t | 2023 | — | flat |
| 83 | Egypt | 0 1000 t | 2023 | — | volatile |
| 83 | Estonia | 0 1000 t | 2023 | — | flat |
| 83 | Finland | 0 1000 t | 2023 | — | flat |
| 83 | Fiji | 0 1000 t | 2023 | — | volatile |
| 83 | Gabon | 0 1000 t | 2023 | — | flat |
| 83 | Georgia | 0 1000 t | 2023 | — | flat |
| 83 | Guinea | 0 1000 t | 2023 | — | flat |
| 83 | Gambia | 0 1000 t | 2023 | — | flat |
| 83 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 83 | Greece | 0 1000 t | 2023 | — | flat |
| 83 | Grenada | 0 1000 t | 2023 | — | flat |
| 83 | Guyana | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Honduras | 0 1000 t | 2023 | — | volatile |
| 83 | Croatia | 0 1000 t | 2023 | — | flat |
| 83 | Haiti | 0 1000 t | 2023 | — | flat |
| 83 | Hungary | 0 1000 t | 2023 | — | flat |
| 83 | Iraq | 0 1000 t | 2023 | — | flat |
| 83 | Iceland | 0 1000 t | 2023 | — | flat |
| 83 | Jamaica | 0 1000 t | 2023 | — | flat |
| 83 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 83 | Cambodia | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Kiribati | 0 1000 t | 2023 | — | volatile |
| 83 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 83 | Kuwait | 0 1000 t | 2023 | — | flat |
| 83 | Lebanon | 0 1000 t | 2023 | — | flat |
| 83 | Libya | 0 1000 t | 2023 | — | volatile |
| 83 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 83 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 83 | Lesotho | 0 1000 t | 2023 | — | flat |
| 83 | Lithuania | 0 1000 t | 2023 | — | flat |
| 83 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 83 | Latvia | 0 1000 t | 2023 | — | flat |
| 83 | Morocco | 0 1000 t | 2023 | — | volatile |
| 83 | Madagascar | 0 1000 t | 2023 | — | flat |
| 83 | Maldives | 0 1000 t | 2023 | — | flat |
| 83 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 83 | North Macedonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Malta | 0 1000 t | 2023 | — | flat |
| 83 | Montenegro | 0 1000 t | 2023 | — | flat |
| 83 | Mongolia | 0 1000 t | 2023 | — | volatile |
| 83 | Mauritania | 0 1000 t | 2023 | — | flat |
| 83 | Namibia | 0 1000 t | 2023 | — | flat |
| 83 | Niger | 0 1000 t | 2023 | — | flat |
| 83 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 83 | Nepal | 0 1000 t | 2023 | — | flat |
| 83 | Nauru | 0 1000 t | 2023 | — | flat |
| 83 | Oman | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Pakistan | 0 1000 t | 2023 | — | flat |
| 83 | Portugal | 0 1000 t | 2023 | — | flat |
| 83 | Paraguay | 0 1000 t | 2023 | — | flat |
| 83 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 83 | Qatar | 0 1000 t | 2023 | — | flat |
| 83 | Romania | 0 1000 t | 2023 | — | flat |
| 83 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 83 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 83 | Serbia | 0 1000 t | 2023 | — | flat |
| 83 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 83 | Suriname | 0 1000 t | 2023 | — | flat |
| 83 | Slovakia | 0 1000 t | 2023 | — | flat |
| 83 | Eswatini | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Seychelles | 0 1000 t | 2023 | — | flat |
| 83 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 83 | Tonga | 0 1000 t | 2023 | — | flat |
| 83 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 83 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 83 | Uganda | 0 1000 t | 2023 | — | flat |
| 83 | Ukraine | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Uruguay | 0 1000 t | 2023 | — | flat |
| 83 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 83 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 83 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 83 | Yemen | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 83 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | flat |
| 83 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 83 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 83 | United Republic of Tanzania | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 14,274 1000 t
- Asia 13,187 1000 t
- Eastern Asia 9,305 1000 t
- South-eastern Asia 3,437 1000 t
- Africa 793 1000 t
- Net Food Importing Developing Countries (NFIDCs) 707 1000 t
- Least Developed Countries (LDCs) 627 1000 t
- Western Africa 542 1000 t
- Low Income Food Deficit Countries (LIFDCs) 424 1000 t
- Southern Asia 422 1000 t
- Land Locked Developing Countries (LLDCs) 291 1000 t
- Eastern Africa 167 1000 t
About this data
A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per capita food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content.